class_docstr: Interpolate Image instance at arbitrary points in world space
  
  The resampling is done with ``scipy.ndimage``.
docstr: Resample image at points in world space
  
  Parameters
  ----------
  points : array
     values in self.image.coordmap.output_coords.  Each row is a point.
  
  Returns
  -------
  V : ndarray
     interpolator of self.image evaluated at points
docstr_tok: ["Resample","image","at","points","in","world","space","Parameters","--","--","--","--","--","points",":","array","values","in","self.image.coordmap.output_coords",".","Each","row","is","a","point",".","Returns","--","--","--","-","V",":","ndarray","interpolator","of","self.image","evaluated","at","points"]
code: def evaluate(self, points):
      """Resample image at points in world space
  
      Parameters
      ----------
      points : array
         values in self.image.coordmap.output_coords.  Each row is a point.
  
      Returns
      -------
      V : ndarray
         interpolator of self.image evaluated at points
      """
      points = np.array(points, np.float64)
      output_shape = points.shape[1:]
      points.shape = (points.shape[0], seq_prod(output_shape))
      cmapi = self.image.coordmap.inverse()
      voxels = cmapi(points.T).T + self._n_prepad
      V = map_coordinates(
          self._data,
          voxels,
          order=self.order,
          mode=self.mode,
          cval=self.cval,
          prefilter=self.order < 2,
      )
      # ndimage.map_coordinates returns a flat array,
      # it needs to be reshaped to the original shape
      V.shape = output_shape
      return V
  
file_path: nipy/nipy/algorithms/interpolation.py
imports: import tempfile
  import numpy
  from scipy.ndimage import map_coordinates, spline_filter
  from ..utils import seq_prod
label_desc: Use image node_id 5 for calling the ImageInterpolator obj's underlying member method code with example usage: obj.evaluate(points) and returns: V